EFFECT OF PHOSPHATE FERTILIZATION AND BASE SATURATION OF SUBSTRATE ON THE SEEDLINGS GROWTH AND QUALITY OF Plathymenia foliolosa Benth.

<div><p>ABSTRACT This study aimed to evaluate the growth and quality of seedlings of Plathymenia foliolosa Benth in response to base saturation of substrate and phosphate fertilization. The treatments were arranged in a factorial design of 6 P levels (0, 120, 240, 360, 480 and 600 mg dm-3) by 5 base saturation levels (3.5, 25, 40, 55, 70 %), in randomized blocks with four replications. The height of aerial part, neck diameter, shoot dry matter, root dry matter and total dry matter were determined at 118 days after the transplanting. It was still calculated the relation shoot dry matter/root dry matter and the Dickson Quality Index. There were significant effects of the phosphate fertilization for all studied variables. The base saturation had influence on all studied variables, except for the shoot dry matter/root dry matter relation. No significant effect of the interaction between base saturation of substrate and phosphate fertilization was observed on seedlings growth and quality. For the studied conditions, it is recommended 300 mg dm-3 of P for the production of quality seedlings of Plathymenia foliolosa without the necessity of liming.</p></div

SITE CLASSIFICATION FOR EUCALYPT STANDS USING ARTIFICIAL NEURAL NETWORK BASED ON ENVIRONMENTAL AND MANAGEMENT FEATURES

<div><p>ABSTRACT Several methods have been proposed to perform site classification for timber production. However, there is frequent need to assess site productive capacity before forest establishment. This has motivated the application of Artificial Neural Networks (ANN) for site classification. Hereby, the traditional guide curve (GC) procedure was compared to the ANN with no stand measures as input. In addition, different ANN settings were tested to assess the best setting. The variables used to train the ANN were: climatic variables, soil types, spacing and genetic material. The results from the ANN and the GC methods were compared to the observed classes, which were defined using the observed dominant high at the age of seven years. The comparison was performed using the Kappa coefficient (K) and descriptive analysis. The results showed that the cost function “Cross Entropy” and the output activation function “Softmax” were the best for this purpose. The ANN classification resulted in substantial agreement with the observed indices against a moderate agreement of the GC procedure. The change in growth patterns throughout the rotation may have hindered the proper classification by the CG method, which does not happen with the ANN. Moreover, the GC method shows efficiency on classification in cases which data from stands at the age close to the reference age are available. Also, it could be possible to improve its accuracy if another advanced regression techniques were applied. However, the ANN method presented here is not sensible to growth instability and allows classifying sites with no plantation history.</p></div

EVALUATION OF NON-LINEAR TAPER EQUATIONS FOR PREDICTING THE DIAMETER OF EUCALYPTUS TREES

<div><p>ABSTRACT This study aims to evaluate non-linear stem taper models for predicting the pre-commercial diameter of eucalyptus trees and to analyze the effect of genotype on stem taper. The treatments comprise three different genotypes of Eucalyptus sp. in a 3 × 3 m plantation spacing. Seventy sample trees aged 10 years were felled for each treatment. The outside bark diameter measurements were taken at 0.5 m; 1.0 m; 1.5 m; 2.0 m, and then at intervals of 2.0 m till the top of the stem. Four non-linear models were evaluated, namely, the sigmoid model of Garay (1979), the variable exponent model of Kozak (1988), the segmented model of Max and Burkhart (1976), and the compatible model of Demaerschalk (1972). The performance of the models was assessed using the following statistical validation methods: correlation coefficient, standard error of estimate, mean bias, bias variance, root mean squared error, and mean absolute deviation. Graphical analysis of residues was used to evaluate the accuracy and precision of the estimates. Compared with other models, the variable exponent model of Kozak (1988) best described the stem profile, and predicted the total volume of the trees. The identity test showed that the stem profile is affected by the genotype.</p></div

A MULTI-AGENT SYSTEM FOR FOREST TRANSPORT ACTIVITY PLANNING

<div><p>ABSTRACT This study aims to propose and implement a conceptual model of an intelligent system in a georeferenced environment to determine the design of forest transport fleets. For this, we used a multi-agent systems based tool, which is the subject of studies of distributed artificial intelligence. The proposed model considers the use of plantation mapping (stands) and forest roads, as well as information about the different vehicle transport capacities. The system was designed to adapt itself to changes that occur during the forest transport operation process, such as the modification of demanded volume or the inclusion of route restrictions used by the vehicles. For its development, we used the Java programming language associated with the LPSolve library for the optimization calculation, the JADE platform to develop agents, and the ArcGis Runtime to determine the optimal transport routes. Five agents were modelled: the transporter, controller, router, loader and unloader agents. The model is able to determine the amount of trucks among the different vehicles available that meet the demand and availability of routes, with a focus on minimizing the total costs of timber transport. The system can also rearrange itself after the transportation routes change during the process.</p></div

ESTIMATION OF HEIGHT OF EUCALYPTUS TREES WITH NEUROEVOLUTION OF AUGMENTING TOPOLOGIES (NEAT)

<div><p>ABSTRACT The aim of this study was to evaluate the method of neuroevolution of augmenting topologies (NEAT) to adjust the weights and the topology of artificial neural networks (ANNs) in the estimation of tree height in a clonal population of eucalyptus, and compare with estimates obtained by a hypsometric regression model. To estimate the total tree height (Ht), the RNAs and the regression model, we used as variables a diameter of 1.3 m height (dbh) and the dominant height (Hd). The RNAs were adjusted and applied to the computer system NeuroForest, varying the size of the initial population (the genetic algorithm parameter) and the density of initial connections. Estimates of the total height of the trees obtained with the use of RNA and the regression model were evaluated based on the correlation coefficient, the percentage of errors scatter plot, the percentage frequency histogram of percentage errors, and the root mean square error (root mean square error - RMSE). Various settings which resulted in superior statistics to the hypsometric regression model were found. Connections had the highest correlation and the lowest RMSE% with a population size value of 300 and an initial density of 0.1 RNA. The NEAT methodology proved effective in estimating the height of trees in clonal population of eucalyptus.</p></div